March 22, 2015

While I admire QlikView's genius associative in-memory engine I'm not a big fan of QlikView's loading script. If QlikView wasn't meant for departmental use, it would not have been a problem. But since QlikView is heavily oriented on business departments with limited IT supporting staff, the necessity to deal with transformation logic encoded in a proprietary script syntax is an obstacle because of several reasons:

It makes it harder to promote QlikView in organizations, since readability of QlikView script is no better than of Visual Basic macros in Excel spreadsheets or SQL.

Since business users usually can't write/read the scripts (they are not supposed to have programming skills), it inflates development and maintenance costs because even minor changes to the logic have to be made by developers and developers have to answer all questions about how this or that is calculated.

Total lack of metadata lineage. To make it even worse, the dollar-sign expansions make it impossible to parse scripts and rebuild abstract syntax tree in external applications.

With QlikSense the situation is even worse, because QlikSense is targeted as a self-service data discovery platform, but the need in loading script makes it dead on arrival.

I believe that data transformation can be done without programming in the vast majority of cases. That's why I designed EasyMorph that can be integrated with both QlikView and QlikSense.

Today we've published an example of QlikView Integration.
It shows how data transformation logic can be moved from a QlikView
loading script into an EasyMorph project, where it can be visually
designed, modified and viewed. While it doesn't replace the loading
script completely (yet) it demonstrates how core transformation logic
can be made accessible for non-technical users, who can now explore and
modify the logic in a visual way, without dealing with the script
syntax.

Here is its transformation logic. Input and output
transformations are marked on the screenshot.

The
logic loads a text file (one file per state), maps state names from
another file, does a few calculations and aggregations, and exports the
result into a QVD file. Here is the loading script with EasyMorph
project integration (comments removed, download the example for the
full version):

//read the QVD generated by the EasyMorph project LOAD *, '$(State)' as State FROM output.qvd (qvd);

NEXT I

Since
EasyMorph can't process a list of files yet (this feature will be added
in future releases) a simple workaround is used -- a cycle, that
iterates through a list of file names, and renaming.

For convenience the EasyMorph project can be opened right from desktop QlikView (in example there is a button for this).

For
server execution, you might need to specify the path to EasyMorph
executable explicitly, since EasyMorph is installed under a user account
and may not be available in the registry under QlikView Server's
account.

While it's not shown in the example, you can
also add a link to the HTML documentation automatically generated by
EasyMorph when it runs a project with /doc parameter from command line (see help on this).
In this case users will be able to see the documentation right in the
web-browser, next to the application. Or, right in the application,
using an extension for web page embedding.

March 5, 2015

Tableau is a great tool. I've been watching it for a few years and I like the way it's developing -- more sophisticated computations, better performance, faster visual engine. Tableau aims at analysts without technical background -- an audience which probably is most under-served in terms of tooling than any other category of office workers. All what they usually have for their data analysis needs is Excel, love it or hate it.

At the same time I struggled to understand the conceptual breakthrough behind Tableau. While it's often considered a prominent Data Discovery platform, when it comes to data transformation it's not significantly less dependent in IT staff than traditional Business Intelligence platforms. Just as traditional BI, Tableau needs well prepared data, preferably residing in a database. And when it comes to databases all user-friendliness ends -- last time when SQL was user-friendly was in 1980s.

In my understanding the reason why Data Discovery started outpacing traditional BI is that it can liberate business teams from dependency on IT folks. Data Discovery tools must be self-sufficient by definition. It means that users should be able to collect, clean, transform and prepare data for analysis themselves. And this is why they still love Excel -- because it makes it possible, because it lets them control. And that's why QlikView is popular -- because it has its own ETL which makes it self-sufficient. While QlikView has its own pros and cons (personally I'm not a big fan of its loading script), but in vast majority of cases it has all you need to prepare your data for visualization and then analyze it. But what about Tableau?

I designed EasyMorph, an easy-to-use ETL tool intended for exactly the same target audience as Tableau -- knowledge workers without a technical background. Like Tableau, EasyMorph is highly visual and it doesn't require SQL skills or programming. Like Tableau, it's fast and lightweight, and it doesn't demand weeks of trainings. My goal is to make EasyMorph a perfect companion for Tableau and allow Tableau to become a truly Data Discovery platform, owned by business users. Today EasyMorph made one more step towards that goal -- we've added support for Tableau Data Extracts.

If you're a Tableau user, give EasyMorph a try -- maybe this is something that you were missing in your Tableau experience. Feel free to drop me a few lines with your thoughts on it. You can find my email in the right sidebar of this blog. Thank you!

About Dmitry Gudkov

I used to be a BI consultant for 12+ years. In 2013 I switched to developing BI/ETL software and created EasyMorph — a new kind of data transformation and analysis tool. I'm also the author of QViewer — a popular standalone QVD file viewer.